Statistical Analytics

Unified communication media streams contain attributes that are both alpha numeric representing fields like extension, dialed number, user ID, IP address, or gateway, as well as numerical fields like duration, volume transferred or received, wait times, hold times, talk times, and others. As an automatic feature of Predictive UC Analytics all numerical fields captured from the session stream are being statistically model for enhanced modeling and triggered notification. Statistical modeling significantly enhances the value of the data being collected and monitored by providing visibility into pattern outliers and by using regression modeling provides foresight into both short-term and long term patterns.

Visibility into outliers is beneficial for multiple reasons including cost control, fraud protection, customer satisfaction, license alignment, and network capacity planning. In addition, using regression models to project future requirements based on historical patterns also increases the value of Predictive UC Analytics by taking the guessing out of business planning.